This article explores how IO-Link is reshaping predictive maintenance and empowering real-time sensor management, elevating the performance of modern industrial operations.
Engineers at the Fraunhofer Institute for Photonic Microsystems (IPMS) here have developed a new system that combines sensor technology, data acquisition and AI-based data evaluation for condition monitoring and predictive maintenance.
WASHINGTON—The National Association of Manufacturers has released a report on artificial intelligence that examines why the technology is important and explains how leading companies are using it to improve productivity.
Equipped with visual, thermal and acoustic sensors, the machine is used to collect valuable data for the plant’s digital twin, while also serving as a watchdog overseeing operations.
Artificial intelligence (AI) has received a lot of attention over recent years. It has also brought awareness to traditional machine vision processes in manufacturing and industrial automation.
How can manufacturers make the critical transition from data to action? How do they effectively navigate the overabundance of data to pick out what’s meaningful? How do they use these insights to drive overall productivity and efficiency in an automotive context?
The answer to these questions involves deploying a three-tiered IIoT approach that provides automotive OEMs and suppliers with a comprehensive digital roadmap for their operations.
For a product to be assembled successfully, it’s essential to move the right parts, to the right place, in the right orientation, at the right time. Motion control technology makes that happen. Here’s a sampling of the latest technology.
The assembly line in Hall M13 at the ŠKODA plant in Mladá Boleslav is one of the Czech carmaker’s busiest. The best-selling ŠKODA Octavia is assembled here, as is the ŠKODA Enyaq iV electric SUV. Every minute of downtime on this line means losses in the form of unproduced cars.